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Text Sentiment Analysis and Classification Based on Bidirectional Gated Recurrent Units (GRUs) Model
This paper explores the importance of text sentiment analysis and classification in the field of natural language processing, and proposes a new approach to sentiment analysis and classification based on the bidirectional gated recurrent units (GRUs) model.
A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentation
In the ever-evolving landscape of social network advertising, the volume and accuracy of data play a critical role in the performance of predictive models.
Regional Style and Color Transfer
This paper presents a novel contribution to the field of regional style transfer.
Exploring Diverse Methods in Visual Question Answering
This study explores innovative methods for improving Visual Question Answering (VQA) using Generative Adversarial Networks (GANs), autoencoders, and attention mechanisms.
Optimizing Contrail Detection: A Deep Learning Approach with EfficientNet-b4 Encoding
In the pursuit of environmental sustainability, the aviation industry faces the challenge of minimizing its ecological footprint.
Confidence-Triggered Detection: Accelerating Real-time Tracking-by-detection Systems
Real-time object tracking necessitates a delicate balance between speed and accuracy, a challenge exacerbated by the computational demands of deep learning methods.
Using an Ancillary Neural Network to Capture Weekends and Holidays in an Adjoint Neural Network Architecture for Intelligent Building Management
To achieve these requirements, we propose a novel adjoint neural network architecture for time series prediction that uses an ancillary neural network to capture weekend and holiday information.
